R and ‘Faster Data’ - Dirk Eddelbuetteldirk.eddelbuettel.com/papers/ism-hpccon-rcpp-fast-date.pdf · R and ‘Faster Data’ TheCaseforRcpp DirkEddelbuettel ISMHPCCON2015&ISMHPConRWorkshop

R and lsquoFaster DatarsquoThe Case for Rcpp

Dirk EddelbuettelISM HPCCON 2015 amp ISM HPC on R WorkshopThe Institute of Statistical Mathematics Tokyo JapanOctober 9 - 12 2015Released under a Creative Commons Attribution-ShareAlike 40 International License

Introduction

A Very Kind Tweet

And Another Tweet

And Yet Another Tweet

And Why Not Another Tweet

And Last But Not Least

Extending R

Why R Programming with Data

ChambersComputationalMethods for DataAnalysis Wiley1977

Becker Chambersand Wilks TheNew S LanguageChapman amp Hall1988

Chambers andHastie StatisticalModels in SChapman amp Hall1992

ChambersProgramming withData Springer1998

ChambersSoftware for DataAnalysisProgramming withR Springer 2008

Thanks to John Chambers for sending me high-resolution scans of the covers of his books

A Simple Example

xx lt- faithful[eruptions]fit lt- density(xx)plot(fit)

A Simple Example

1 2 3 4 5 6

densitydefault(x = xx)

N = 272 Bandwidth = 03348

A Simple Example - Refined

xx lt- faithful[eruptions]fit1 lt- density(xx)fit2 lt- replicate(10000

x lt- sample(xxreplace=TRUE)density(x from=min(fit1$x) to=max(fit1$x))$y

)fit3 lt- apply(fit2 1 quantilec(00250975))plot(fit1 ylim=range(fit3))polygon(c(fit1$xrev(fit1$x)) c(fit3[1]rev(fit3[2]))

col=grey border=F)lines(fit1)

1 2 3 4 5 6

So Why R

R enables us to

middot work interactivelymiddot explore and visualize datamiddot access retrieve andor generate datamiddot summarize and report into pdf html hellip

making it the key language for statistical computing and apreferred environment for many data analysts

So Why R

R has always been extensible via

middot C via a bare-bones interface described in Writing RExtensions

middot Fortran which is also used internally by Rmiddot Java via rJava by Simon Urbanekmiddot C++ but essentially at the bare-bones level of C

So while in theory this always worked ndash it was tedious inpractice

Why Extend R

Chambers (2008) opens Chapter 11 Interfaces I Using C andFortran

Since the core of R is in fact a program written inthe C language itrsquos not surprising that the mostdirect interface to non-R software is for code writtenin C or directly callable from C All the sameincluding additional C code is a serious step withsome added dangers and often a substantial amountof programming and debugging required You shouldhave a good reason

Why Extend R

Chambers proceeds with this rough map of the road ahead

middot Againstmiddot Itrsquos more workmiddot Bugs will bitemiddot Potential platform dependencymiddot Less readable software

middot In Favormiddot New and trusted computationsmiddot Speedmiddot Object references

Why Extend R

The Why boils down to

middot speed Often a good enough reason for us hellip and a focusfor us in this workshop

middot new things We can bind to libraries and tools that wouldotherwise be unavailable in R

middot references Chambers quote from 2008 foreshadowed thework on Reference Classes now in R and built upon viaRcpp Modules Rcpp Classes (and also RcppR6)

And Why C++

middot Asking Google leads to about ~ 50 million hitsmiddot Wikipedia C++ is a statically typed free-form

multi-paradigm compiled general-purpose powerfulprogramming language

middot C++ is industrial-strength vendor-independentwidely-used and still evolving

middot In science amp research one of the most frequently-usedlanguages If there is something you want to use connect to it probably has a CC++ API

middot As a widely used language it also has good tool support(debuggers profilers code analysis)

Why C++

Scott Meyers View C++ as a federation of languages

middot C provides a rich inheritance and interoperability as UnixWindows hellip are all build on C

middot Object-Oriented C++ (maybe just to provide endlessdiscussions about exactly what OO is or should be)

middot Templated C++ which is mighty powerful template metaprogramming unequalled in other languages

middot The Standard Template Library (STL) is a specifictemplate library which is powerful but has its ownconventions

middot C++11 (and C++14 and beyond) add enough to becalled a fifth language

NB Meyers original list of four languages appeared years before C++11 2173

Why C++

middot Mature yet currentmiddot Strong performance focus

middot You donrsquot pay for what you donrsquot usemiddot Leave no room for another language between the

machine level and C++

middot Yet also powerfully abstract and high-levelmiddot C++11 is a big deal giving us new language featuresmiddot While there are complexities Rcpp users are mostly

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

R offers us the best of both worlds

middot Compiled code withmiddot Access to proven libraries and algorithms in

CC++Fortranmiddot Extremely high performance (in both serial and parallel

modes)middot Interpreted code with

middot An accessible high-level language made for Programmingwith Data

middot An interactive workflow for data analysismiddot Support for rapid prototyping research and

experimentation2573

Why Rcpp

middot Easy to learn as it really does not have to be thatcomplicated ndash we will see numerous few examples

middot Easy to use as it avoids build and OS system complexitiesthanks to the R infrastrucure

middot Expressive as it allows for vectorised C++ using RcppSugar

middot Seamless access to all R objects vector matrix listS3S4RefClass Environment Function hellip

middot Speed gains for a variety of tasks Rcpp excels preciselywhere R struggles loops function calls hellip

middot Extensions greatly facilitates access to external librariesusing eg Rcpp modules

Getting Started

sourceCpp Jumping Right In

RStudio makes starting very easy

A First Example Contrsquoed

The following file gets createdinclude ltRcpphgtusing namespace Rcpp

This is a simple example of exporting a C++ function to R You can source this function into an R session using the RcppsourceCpp function (or via the Source button on the editor toolbar)

[[Rcppexport]]NumericVector timesTwo(NumericVector x)

return x 2

You can include R code blocks in C++ files processed with sourceCpp (useful for testing and development) The R code will be automatically run after the compilation

RtimesTwo(42)

So what just happened

middot We defined a simple C++ functionmiddot It operates on a numeric vector argumentmiddot We asked Rcpp to lsquosource itrsquo for usmiddot Behind the scenes Rcpp creates a wrappermiddot Rcpp then compiles links and loads the wrappermiddot The function is available in R under its C++ name

Try it

middot Save the file as say timesTwocppmiddot You could a temporary directory or a projects directory

or your desktop (keep it simple)middot Either press the Source button or callsourceCpp(thefilecpp) to compile it

middot Then at the R prompt

simpletimesTwo(21) more interestingtimesTwo(c(12344101))

cppFunction

cppFunction() creates compiles and links a C++ file andcreates an R function to access it

cppFunction(int times2(int x) return 2x )times2(21) same identifier as C++ function

evalCpp

evalCpp() evaluates a single C++ expression Includes anddependencies can be declared

This allows us to quickly check C++ constructs

library(Rcpp)evalCpp(2 + 2) simple test

evalCpp(stdnumeric_limitsltdoublegtmax())

[1] 1797693e+308

Speed Example (due to StackOverflow)

Consider a function defined as

f(n) such that n when n lt 2

f(n minus 1) + f(n minus 2) when n ge 2

Speed Example in R

R implementation and use

f lt- function(n) if (n lt 2) return(n)return(f(n-1) + f(n-2))

Using it on first 11 argumentssapply(010 f)

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

library(rbenchmark)benchmark(f(10) f(15) f(20))[14]

test replications elapsed relative 1 f(10) 100 0023 1000 2 f(15) 100 0542 23565 3 f(20) 100 6172 268348

Speed Example in C C++

A C or C++ solution can be equally simple

int g(int n) if (n lt 2) return(n)return(g(n-1) + g(n-2))

But how do we call it from R

Mattrsquos Example from useR 2015include ltRhgtinclude ltRinternalshgt

int fibonacci_c_impl(int n) if (n lt 2) return nreturn fibonacci_c_impl(n - 1) + fibonacci_c_impl(n - 2)

SEXP fibonacci_c(SEXP n) SEXP result = PROTECT(allocVector(INTSXP 1))INTEGER(result)[0] = fibonacci_c_impl(asInteger(n))UNPROTECT(1)return result

need to compile link load fibonacci lt- function(n) Call(fibonacci_c n)sapply(010 fibonacci) 3973

One Minor Modification to Mattrsquos Exampleinclude ltRhgtinclude ltRinternalshgt

[[Rcppexport]]SEXP fibonacci_c(SEXP n)

SEXP result = PROTECT(allocVector(INTSXP 1))INTEGER(result)[0] = fibonacci_c_impl(asInteger(n))UNPROTECT(1)return result

Rsapply(010 fibonacci_c)

But Rcpp makes this much easier

RcppcppFunction(int g(int n) if (n lt 2) return(n)return(g(n-1) + g(n-2)) )

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Comparing R and C++

Timing

library(rbenchmark)benchmark(f(25) g(25) order=relative)[14]

test replications elapsed relative 2 g(25) 100 020 10 1 f(25) 100 6622 3311

A nice gain of a few orders of magnitude4273

Another Angle on Speed

Run-time performance is just one example

Time to code is another metric

We feel quite strongly that helps you code more succinctlyleading to fewer bugs and faster development

A good environment helps RStudio integrates R and C++development quite nicely (eg the compiler error messageparsing is very helpful) and also helps with package building

Speed Example Footnote Also Due to Matt

include ltRcpphgt

[[Rcppplugins(cpp11)]]

constexpr int fibonacci_recursive_constexpr(const int n) return n lt 2 n (fibonacci_recursive_constexpr(n - 1) +

fibonacci_recursive_constexpr(n - 2))

[[Rcppexport]]int constexprFib()

const int N = 42constexpr int result = fibonacci_recursive_constexpr(N)return result

Popularity

Used by 483 CRAN Packages as of this week

Page Rank One (According to Andrie de Vries)

Case Study

Time Series Dashboard

Previous Status

middot We have a lot of data circulating at workmiddot Market prices positions risk estimates profitloss hellipmiddot The used to be displayed in a one-off lsquodisplay gridrsquomiddot But no history and no plots

Easy R Fix

middot Use Redis to cache datamiddot Redis is simple well-established widely usedmiddot Excellent R package rredis by Bryan Lewismiddot Use Shiny to access Redis and create lsquodashboardsrsquomiddot We need to be fast enough to keep users engagedmiddot Goal is ~ 250 msec (in-line with web UI research)

What does Redis do

middot Essentially a very fast and lightweight keyvalue storemiddot After SET key valuemiddot Do GET key to retrieve value

middot APIs for multiple languages CC++ Python Java hellipmiddot Can also store lists sets hellipmiddot Can be coaxed to provide simple columnar data storemiddot Basic access store strings retrieve strings

What is wrong with that

middot String conversion lsquoexpensiversquo when done repeatedly for afew thousand points

middot Do string conversion in compiled code ndash RcppRedismiddot A step better R serialization and deserialization using

RApiSerialize

Getting Data

library(Quandl)Quandlapi_key(yourAPIkeyhere) register obtain key anon possible toosp lt- Quandl(CHRISCME_SP1 type=xts)saveRDS(sp file=dataquandl-sp1rds) longer serieses lt- Quandl(CHRISCME_ES1 type=xts)saveRDS(sp file=dataquandl-es1rds) more activehead(sp 3)

Time Series Dashboard Monthly Plot

Apr1982

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Oct2015

SP Apr 1982 Oct 2015

Setter Version 1 via rredis

insertXtsR lt- function(x key) xm lt- coredata(x)xi lt- asinteger(index(x))for (i in seq_len(nrow(xm)))

dat lt- unname(c(xi[i] xm[i drop=TRUE]))redisRPush(key dat)

invisible(NULL)

Getter Base Version via rredis

getXtsR lt- function(key) n lt- asinteger(redisLLen(key))vals lt- redisLRange(key 0 n)m lt- length(vals)mat lt- matrix(NA n 8)dat lt- rep(NA n)for (i in 1n)

z lt- vals[[i]]dat[i] lt- z[1]mat[i ] lt- z[-1]

x lt- xts(mat orderby=asDate(dat origin=1970-01-01))colnames(x) lt- colnamsx

Getter Rcpp Version 1

getXtsRcpp1 lt- function(key) n lt- asinteger(redis$llen(key))vals lt- redis$lrange(key 0 n)m lt- length(vals)mat lt- matrix(NA n 8)dat lt- rep(NA n)for (i in 1n)

getXtsRcpp2 lt- function(key) mat lt- redis$listToMatrix(redis$lrange(key 0 -1))x lt- xts(mat[-1] orderby=asDate(mat[1] origin=1970-01-01))colnames(x) lt- colnamsx

Timings

key lt- quandlcmesp1res lt- benchmark(getXtsR(key)

getXtsRcpp1(key)getXtsRcpp2(key)order=relative replications=25)[14]

print(res)

test replications elapsed relative 3 getXtsRcpp2(key) 25 0608 1000 2 getXtsRcpp1(key) 25 1768 2908 1 getXtsR(key) 25 29063 47801

Can we do better

middot Yes Redis also offers a binary typemiddot We grab each data row as a vectormiddot Pointer plus length a common form of expression

New Rcpp Function R Side

insertXtsRcpp lt- function(x key) xm lt- coredata(x)xi lt- asnumeric(index(x))dat lt- unname(cbind(xi xm))for (i in seq_len(nrow(xm)))

redis$listRPush(key dat[i])invisible(NULL)

New Rcpp Function Setter

redis append to list -- without R serializationstdstring listRPush(stdstring key RcppNumericVector x)

uses binary protocol see hiredis docsredisReply reply =

static_castltredisReplygt(redisCommand(prc_ RPUSH s bkeyc_str()xbegin() xsize()szdb))

stdstring res = freeReplyObject(reply)return(res)

New Rcpp Function Getter

redis get from list from start to end -- without R serializationRcppList listRange(stdstring key int start int end)

redisReply reply =static_castltredisReplygt(redisCommand(prc_ LRANGE s d d

keyc_str() start end))checkReplyType(reply replyArray_t) ensure we got arrayunsigned int len = reply-gtelementsRcppList x(len)for (unsigned int i = 0 i lt len i++)

checkReplyType(reply-gtelement[i] replyString_t) ensure binaryint nc = reply-gtelement[i]-gtlenRcppNumericVector v(ncszdb)memcpy(vbegin() reply-gtelement[i]-gtstr nc)x[i] = v

freeReplyObject(reply)return(x)

Use This Way

getXtsRcpp3 lt- function(key) mat lt- redis$listToMatrix(redis$listRange(key 0 -1))x lt- xts(mat[-1] orderby=asDate(mat[1] origin=1970-01-01))colnames(x) lt- colnamsx

Timings

key2 lt- quandlcmesp1rcppres2 lt- benchmark(getXtsR(key)

getXtsRcpp1(key)getXtsRcpp2(key)getXtsRcpp3(key2)order=relative replications=25)[14]

print(res2)

test replications elapsed relative 4 getXtsRcpp3(key2) 25 0364 1000 3 getXtsRcpp2(key) 25 0582 1599 2 getXtsRcpp1(key) 25 1747 4799 1 getXtsR(key) 25 29481 80992

Status

middot Not so bad ~ 80-fold increase for RcppRedis over rredismiddot Inner retrieval (outside of xts creation) about 100 times

fastermiddot 25 retrieval in 364 msec is clearly lsquogood enoughrsquomiddot Limitation Storing small binary vectors not elegantmiddot Possible fix MessagePackmiddot Alternative to lsquobinary JSONrsquo and alternativemiddot Easy to use API

Simple MessagePack buffer creation then sendingMessagePack buffer as binary load

typedef msgpacktypetupleltdouble int int intgt msg_t

msgpacksbuffer buffermsg_t m(v[0] (int)v[1] (int)v[2] (int)v[3]) fill the message typemsgpackpack(buffer m) and pack it

replynew =static_castltredisReplygt(redisCommand(d RPUSH s b

keyc_str()bufferdata() buffersize()))

freeReplyObject(replynew)

Conclusion

middot Simple things remain simplemiddot Memory allocation loops conversions hellip faster in C++middot Yet easily accessible from Rmiddot Leverage R strength (eg shiny) by overcoming bottlenecksmiddot Leads to Seamless Integration of R and C++ for

accelerated modeling

The End

Documentation

middot The Rcpp package comes with nine pdf vignettes andnumerous help pages

middot The introductory vignettes are now published (for Rcppand RcppEigen in J Stat Software for RcppArmadillo inComp Stat amp Data Anlys)

middot The rcpp-devel list is the recommended resourcegenerally very helpful and fairly low volume

middot StackOverflow has over 900 posts too and Andmiddot A number of blog posts introducediscuss features

Rcpp Gallery

The Rcpp book

Very Last Words

Thank Youdirkeddelbuettelcom

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Introduction

A Very Kind Tweet

And Another Tweet

Extending R

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

A Very Kind Tweet

And Another Tweet

Extending R

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

And Another Tweet

Extending R

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Extending R

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Extending R

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Extending R

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Extending R

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

A Simple Example

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

1 2 3 4 5 6

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

So Why R

R enables us to

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

So Why R

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Why Extend R

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

And Why C++

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Why C++

shielded

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Interface Vision

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Bell Labs May 1976

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Interface Vision

experimentation2573

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Why Rcpp

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Getting Started

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

return x 2

RtimesTwo(42)

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Try it

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

cppFunction

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

evalCpp

[1] 1797693e+308

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Speed Example in R

[1] 0 1 1 2 3 5 8 13 21 34 55

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Speed Example Timed

Timing

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

sapply(010 g)

[1] 0 1 1 2 3 5 8 13 21 34 55

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Timing

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

include ltRcpphgt

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Popularity

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Case Study

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Previous Status

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Easy R Fix

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

What does Redis do

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

RApiSerialize

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Getting Data

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Apr1982

Jan1984

Jan1986

Jan1988

Jan1990

Jan1992

Jan1994

Jan1996

Jan1998

Jan2000

Jan2002

Jan2004

Jan2006

Jan2008

Jan2010

Jan2012

Jan2014

Oct2015

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

invisible(NULL)

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Timings

print(res)

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Can we do better

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Use This Way

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Timings

print(res2)

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Status

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Conclusion

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Documentation

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Rcpp Gallery

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

The Rcpp book

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Very Last Words

Introduction

Extending R

Interface Vision

Getting Started

Popularity

Case Study

The End

Documents

R and ‘Faster Data’ - Dirk Eddelbuetteldirk.eddelbuettel.com/papers/ism-hpccon-rcpp-fast-date.pdf · R and ‘Faster Data’ TheCaseforRcpp DirkEddelbuettel ISMHPCCON2015&ISMHPConRWorkshop